Model-Driven Engineering Practices Research Articles

A survey on modeling and model-driven engineering practices in the embedded software industry

Abstract Software-intensive embedded systems have become an essential aspect of our lives. To cope with its growing complexity, modeling and model-driven engineering (MDE) are widely used for analysis, design, implementation, and testing of these systems. Since a large variety of software modeling practices is used in the domain of embedded software, it is important to understand and characterize the-state-of-the-practices and also the benefits, challenges and consequences of using software modeling approaches in this domain. The goal of this study is to investigate those practices in the embedded software engineering projects by identifying to what degree, why and how software modeling and MDE are used. To achieve this objective, we designed and conducted an online survey. Opinions of 627 practicing embedded software engineers from 27 different countries are included in the survey. The survey results reveal important and interesting findings about the state of software modeling and MDE practices in the worldwide embedded software industry. Among the results: (1) Different modeling approaches (from informal sketches to formalized models) are widely used in the embedded software industry with different needs and all of the usages could be effective depending on the various modeling characteristics; (2) The majority of participants use UML; and the second most frequently selected response is “Sketch/No formal modeling language”, which shows the wide-spread informal usage of modeling; (3) In model-driven approaches, it is not so important to have a graphical syntax to represent the model (as in UML) and depending on the type of target embedded industrial sector, modeling stakeholders prefer models, which can be represented in a format that is readable by a machine (as in DSL); (4) Sequence diagrams and state-machines are the two most popular diagram types; (5) Top motivations for adopting MDE are: cost savings, achieving shorter development time, reusability and quality improvement. The survey results will shed light on the state of software modeling and MDE practices and provide practical benefits to embedded software professionals (e.g., practitioners, researchers and also educators).

On the use of model-driven engineering principles for the management of simulation experiments

Simulation experiments are an essential part of computational science and engineering. The use of simulation models is widely adopted by practitioners from diverse areas of applied sciences. Nevertheless, simulations are rarely replicated due to reuse and maintenance challenges related to models and data. In this respect, we propose that crucial and labor intensive parts of simulation experiments could be supported by model transformations. This work focuses on model-driven engineering practices to enable replicable and reusable simulation experiments. These practices are used to devote researchers’ time to analyze the system under investigation rather than dealing with low level details to create a working environment. The results of our framework development work are presented.

Considerations about quality in model-driven engineering

The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.

On submodels and submetamodels with their relation

Model-driven engineering (MDE) recognized software models as first-class objects with their own relationships and operations, up to constitute full structured model spaces. We focus on inclusion capacities through the concepts of submodel and submetamodel which contribute a lot to the structuring effort. Submodels and submetamodels underlie many MDE practices which require their precise characterization for plain control. A typical application is model management as offered by model repositories. On the basis of results on submodel inclusion we stated in a preceding paper, we concentrate on the special form of submodels which are submetamodels and their specific role in model space structuring. Pointing out that relating submodels and submetamodels is two ways, their respective inclusion hierarchies will be systematically characterized and symmetrically compared under the logical relationships of metamodel membership and model well-formedness. As a major result, it will be shown that submodel well-formedness w.r.t submetamodels closely relates to submodel invariance (a property which guarantees transitive structure preservation) applied at both levels. The uniform formalization offers algebraic grounding to better comprehension and control of model spaces which underlie MDE activities. At a much more practical level, reusable technology which takes advantage of established results will be offered.

Model-driven engineering practices in industry: Social, organizational and managerial factors that lead to success or failure

In this article, we attempt to address the relative absence of empirical studies of model driven engineering (MDE) in two different but complementary ways. First, we present an analysis of a large online survey of MDE deployment and experience that provides some rough quantitative measures of MDE practices in industry. Second, we supplement these figures with qualitative data obtained from some semi-structured, in-depth interviews with MDE practitioners, and, in particular, through describing the practices of four commercial organizations as they adopted a model driven engineering approach to their software development practices. Using in-depth semi-structured interviewing, we invited practitioners to reflect on their experiences and selected four to use as exemplars or case studies. In documenting some details of their attempts to deploy model driven practices, we identify a number of factors, in particular the importance of complex organizational, managerial and social factors–as opposed to simple technical factors–that appear to influence the relative success, or failure, of the endeavor. Three of the case study companies describe genuine success in their use of model driven development, but explain that as examples of organizational change management, the successful deployment of model driven engineering appears to require: a progressive and iterative approach; transparent organizational commitment and motivation; integration with existing organizational processes and a clear business focus.

From subsets of model elements to submodels

Model-driven engineering (MDE) generalized the status of models from documentation or model-driven architecture (MDA) modeling steps to full artifacts, members of a so-called structured “model space”. We concentrate here on the submodel relationship which contributes a lot to this structuring effort. Many works and MDE practices resort to this notion and call for its precise characterization, which is the intent of this paper. A typical situation is model management through repositories. We start from the definition of a model as a set of model elements plus a set of dependency constraints that it asserts over these elements. This allows to isolate the notions of closed, covariant and invariant submodels. As a major result, we show that submodel transitivity can be guaranteed thanks to submodel invariance. This formalization offers keys to analyze operations which manipulate submodels. For example, we deeply study the operator which consists in extracting a model from another one, when selecting some subset of its elements. The same can be applied to many other model operations and the last part of the paper is dedicated to a synthesis on related works which could profit from this characterization. More practically, we show how the results were exploited in our Eclipse modeling environment.

Large-scale Model-Driven Engineering of web user interaction: The WebML and WebRatio experience

This paper reports the experience of WebRatio, a company focusing on Model-Driven Engineering (MDE) tools (WebRatio and WebRatio BPM) and services since 2001. The adopted MDE approach is based on the transformation of models expressed in a Domain Specific Language called WebML (Web Modeling Language) into running applications, with the unique feature of creating not only the back-end data and business logic but also the Web/RIA front-end, without posing any limitation on the graphical and interaction quality of the user interface. WebRatio has been applied in many industrial projects, some of which have delivered large-scale enterprise applications, generated and maintained completely through MDE practices over the years. In this paper we present the lessons learned within this experience, describe some success stories and show some quantitative information and evaluation on the usage of the approach.

The MDE Diploma: first international postgraduate specialization in model-driven engineering

Model-Driven Engineering (MDE) is changing the way we build, operate, and maintain our software-intensive systems. Several projects using MDE practices are reporting significant improvements in quality and performance but, to be able to handle these projects, software engineers need a set of technical and interpersonal skills that are currently not widely available. The MDE postgraduate diploma intends to fill this gap by offering a full-time one year formation onMDE. The course syllabus is designed to teach students how to work at a higher abstraction level by the rigorous use of (software) models as the main artifacts in all software engineering activities. Contents include the conceptual framework of MDE plus all techniques and tools (e.g. for defining modeling languages, models, and model transformations) required to successfully complete software engineering projects following a MDE approach. The organizational impact (and challenges) of adopting MDE are exemplified using real industrial experiences. This article describes the MDE Diploma and the lessons that we learned after completing its first edition.